353 lines
9.8 KiB
Markdown
353 lines
9.8 KiB
Markdown
---
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name: "product-manager-toolkit"
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description: Comprehensive toolkit for product managers including RICE prioritization, customer interview analysis, PRD templates, discovery frameworks, and go-to-market strategies. Use for feature prioritization, user research synthesis, requirement documentation, and product strategy development.
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---
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# Product Manager Toolkit
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Essential tools and frameworks for modern product management, from discovery to delivery.
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---
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## Table of Contents
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- [Quick Start](#quick-start)
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- [Core Workflows](#core-workflows)
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- [Feature Prioritization](#feature-prioritization-process)
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- [Customer Discovery](#customer-discovery-process)
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- [PRD Development](#prd-development-process)
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- [Tools Reference](#tools-reference)
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- [RICE Prioritizer](#rice-prioritizer)
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- [Customer Interview Analyzer](#customer-interview-analyzer)
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- [Input/Output Examples](#inputoutput-examples)
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- [Integration Points](#integration-points)
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- [Common Pitfalls](#common-pitfalls-to-avoid)
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---
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## Quick Start
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### For Feature Prioritization
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```bash
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# Create sample data file
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python scripts/rice_prioritizer.py sample
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# Run prioritization with team capacity
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python scripts/rice_prioritizer.py sample_features.csv --capacity 15
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```
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### For Interview Analysis
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```bash
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python scripts/customer_interview_analyzer.py interview_transcript.txt
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```
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### For PRD Creation
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1. Choose template from `references/prd_templates.md`
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2. Fill sections based on discovery work
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3. Review with engineering for feasibility
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4. Version control in project management tool
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---
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## Core Workflows
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### Feature Prioritization Process
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```
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Gather → Score → Analyze → Plan → Validate → Execute
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```
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#### Step 1: Gather Feature Requests
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- Customer feedback (support tickets, interviews)
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- Sales requests (CRM pipeline blockers)
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- Technical debt (engineering input)
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- Strategic initiatives (leadership goals)
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#### Step 2: Score with RICE
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```bash
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# Input: CSV with features
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python scripts/rice_prioritizer.py features.csv --capacity 20
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```
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See `references/frameworks.md` for RICE formula and scoring guidelines.
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#### Step 3: Analyze Portfolio
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Review the tool output for:
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- Quick wins vs big bets distribution
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- Effort concentration (avoid all XL projects)
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- Strategic alignment gaps
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#### Step 4: Generate Roadmap
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- Quarterly capacity allocation
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- Dependency identification
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- Stakeholder communication plan
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#### Step 5: Validate Results
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**Before finalizing the roadmap:**
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- [ ] Compare top priorities against strategic goals
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- [ ] Run sensitivity analysis (what if estimates are wrong by 2x?)
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- [ ] Review with key stakeholders for blind spots
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- [ ] Check for missing dependencies between features
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- [ ] Validate effort estimates with engineering
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#### Step 6: Execute and Iterate
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- Share roadmap with team
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- Track actual vs estimated effort
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- Revisit priorities quarterly
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- Update RICE inputs based on learnings
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---
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### Customer Discovery Process
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```
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Plan → Recruit → Interview → Analyze → Synthesize → Validate
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```
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#### Step 1: Plan Research
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- Define research questions
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- Identify target segments
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- Create interview script (see `references/frameworks.md`)
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#### Step 2: Recruit Participants
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- 5-8 interviews per segment
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- Mix of power users and churned users
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- Incentivize appropriately
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#### Step 3: Conduct Interviews
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- Use semi-structured format
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- Focus on problems, not solutions
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- Record with permission
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- Take minimal notes during interview
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#### Step 4: Analyze Insights
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```bash
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python scripts/customer_interview_analyzer.py transcript.txt
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```
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Extracts:
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- Pain points with severity
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- Feature requests with priority
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- Jobs to be done patterns
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- Sentiment and key themes
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- Notable quotes
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#### Step 5: Synthesize Findings
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- Group similar pain points across interviews
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- Identify patterns (3+ mentions = pattern)
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- Map to opportunity areas using Opportunity Solution Tree
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- Prioritize opportunities by frequency and severity
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#### Step 6: Validate Solutions
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**Before building:**
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- [ ] Create solution hypotheses (see `references/frameworks.md`)
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- [ ] Test with low-fidelity prototypes
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- [ ] Measure actual behavior vs stated preference
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- [ ] Iterate based on feedback
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- [ ] Document learnings for future research
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---
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### PRD Development Process
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```
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Scope → Draft → Review → Refine → Approve → Track
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```
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#### Step 1: Choose Template
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Select from `references/prd_templates.md`:
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| Template | Use Case | Timeline |
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|----------|----------|----------|
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| Standard PRD | Complex features, cross-team | 6-8 weeks |
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| One-Page PRD | Simple features, single team | 2-4 weeks |
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| Feature Brief | Exploration phase | 1 week |
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| Agile Epic | Sprint-based delivery | Ongoing |
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#### Step 2: Draft Content
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- Lead with problem statement
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- Define success metrics upfront
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- Explicitly state out-of-scope items
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- Include wireframes or mockups
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#### Step 3: Review Cycle
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- Engineering: feasibility and effort
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- Design: user experience gaps
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- Sales: market validation
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- Support: operational impact
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#### Step 4: Refine Based on Feedback
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- Address technical constraints
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- Adjust scope to fit timeline
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- Document trade-off decisions
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#### Step 5: Approval and Kickoff
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- Stakeholder sign-off
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- Sprint planning integration
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- Communication to broader team
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#### Step 6: Track Execution
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**After launch:**
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- [ ] Compare actual metrics vs targets
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- [ ] Conduct user feedback sessions
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- [ ] Document what worked and what didn't
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- [ ] Update estimation accuracy data
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- [ ] Share learnings with team
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---
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## Tools Reference
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### RICE Prioritizer
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Advanced RICE framework implementation with portfolio analysis.
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**Features:**
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- RICE score calculation with configurable weights
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- Portfolio balance analysis (quick wins vs big bets)
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- Quarterly roadmap generation based on capacity
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- Multiple output formats (text, JSON, CSV)
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**CSV Input Format:**
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```csv
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name,reach,impact,confidence,effort,description
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User Dashboard Redesign,5000,high,high,l,Complete redesign
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Mobile Push Notifications,10000,massive,medium,m,Add push support
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Dark Mode,8000,medium,high,s,Dark theme option
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```
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**Commands:**
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```bash
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# Create sample data
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python scripts/rice_prioritizer.py sample
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# Run with default capacity (10 person-months)
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python scripts/rice_prioritizer.py features.csv
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# Custom capacity
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python scripts/rice_prioritizer.py features.csv --capacity 20
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# JSON output for integration
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python scripts/rice_prioritizer.py features.csv --output json
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# CSV output for spreadsheets
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python scripts/rice_prioritizer.py features.csv --output csv
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```
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---
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### Customer Interview Analyzer
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NLP-based interview analysis for extracting actionable insights.
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**Capabilities:**
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- Pain point extraction with severity assessment
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- Feature request identification and classification
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- Jobs-to-be-done pattern recognition
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- Sentiment analysis per section
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- Theme and quote extraction
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- Competitor mention detection
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**Commands:**
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```bash
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# Analyze interview transcript
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python scripts/customer_interview_analyzer.py interview.txt
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# JSON output for aggregation
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python scripts/customer_interview_analyzer.py interview.txt json
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```
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---
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## Input/Output Examples
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→ See references/input-output-examples.md for details
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## Integration Points
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Compatible tools and platforms:
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| Category | Platforms |
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|----------|-----------|
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| **Analytics** | Amplitude, Mixpanel, Google Analytics |
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| **Roadmapping** | ProductBoard, Aha!, Roadmunk, Productplan |
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| **Design** | Figma, Sketch, Miro |
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| **Development** | Jira, Linear, GitHub, Asana |
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| **Research** | Dovetail, UserVoice, Pendo, Maze |
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| **Communication** | Slack, Notion, Confluence |
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**JSON export enables integration with most tools:**
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```bash
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# Export for Jira import
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python scripts/rice_prioritizer.py features.csv --output json > priorities.json
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# Export for dashboard
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python scripts/customer_interview_analyzer.py interview.txt json > insights.json
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```
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---
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## Common Pitfalls to Avoid
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| Pitfall | Description | Prevention |
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|---------|-------------|------------|
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| **Solution-First** | Jumping to features before understanding problems | Start every PRD with problem statement |
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| **Analysis Paralysis** | Over-researching without shipping | Set time-boxes for research phases |
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| **Feature Factory** | Shipping features without measuring impact | Define success metrics before building |
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| **Ignoring Tech Debt** | Not allocating time for platform health | Reserve 20% capacity for maintenance |
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| **Stakeholder Surprise** | Not communicating early and often | Weekly async updates, monthly demos |
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| **Metric Theater** | Optimizing vanity metrics over real value | Tie metrics to user value delivered |
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---
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## Best Practices
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**Writing Great PRDs:**
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- Start with the problem, not the solution
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- Include clear success metrics upfront
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- Explicitly state what's out of scope
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- Use visuals (wireframes, flows, diagrams)
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- Keep technical details in appendix
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- Version control all changes
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**Effective Prioritization:**
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- Mix quick wins with strategic bets
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- Consider opportunity cost of delays
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- Account for dependencies between features
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- Buffer 20% for unexpected work
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- Revisit priorities quarterly
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- Communicate decisions with context
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**Customer Discovery:**
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- Ask "why" five times to find root cause
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- Focus on past behavior, not future intentions
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- Avoid leading questions ("Wouldn't you love...")
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- Interview in the user's natural environment
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- Watch for emotional reactions (pain = opportunity)
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- Validate qualitative with quantitative data
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---
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## Quick Reference
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```bash
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# Prioritization
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python scripts/rice_prioritizer.py features.csv --capacity 15
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# Interview Analysis
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python scripts/customer_interview_analyzer.py interview.txt
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# Generate sample data
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python scripts/rice_prioritizer.py sample
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# JSON outputs
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python scripts/rice_prioritizer.py features.csv --output json
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python scripts/customer_interview_analyzer.py interview.txt json
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```
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---
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## Reference Documents
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- `references/prd_templates.md` - PRD templates for different contexts
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- `references/frameworks.md` - Detailed framework documentation (RICE, MoSCoW, Kano, JTBD, etc.)
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